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Behavox is a data operating platform that helps multinational enterprises organize and act on enterprise data for risk management, compliance, and revenue optimization. The company specializes in multilingual, AI/ML-based solutions for financial services and regulatory compliance.
You will be an experienced individual contributor in the Subject Matter Expert (SME) team, owning one or two related asset classes. Your primary responsibility is ensuring that the Behavox Financial Data Model (BFDM) and Unified Risk Taxonomy (URT) accurately reflect how trading desks, venues, and regulation operate. The URT serves as the common language for risks across preventive controls (conflicts of interest, conduct) and detective controls (trade and communications surveillance).
Working with minimal day-to-day instruction, you will define asset class data specifications, translate market abuse typologies into scenarios for Polaris (the trade surveillance product), and advise product, engineering, and data science teams. You will support the revenue team in client meetings, demos, and RFPs alongside a senior SME or manager, but will not independently lead engagements with high-profile prospects or regulators.
The role is AI-native: you will work with AI agents and agentic workflows—not just chat assistants—specifying requirements for agent-based pipelines and validating outputs through structured data models and Git-based workflows.
Key responsibilities include:
- Defining BFDM fields, schemas, and validation rules for owned asset classes, and validating data outputs
- Converting market abuse typologies into Polaris risk scenarios, anchoring them to regulatory enforcement cases, and validating outputs with engineering and data science teams
- Mapping owned asset classes to URT risk situations and regulatory requirements, keeping coverage current
- Answering front office, data, and surveillance questions in client meetings, demos, and RFPs; producing SME-reviewed collateral
- Writing clear specifications for agent-based pipelines, reviewing and validating outputs, and contributing changes through Git-based workflows in GitLab
This is a remote-friendly role open to candidates within Italy.
**Requirements:**
- 5+ years of hands-on experience in a front office role, market surveillance, or front office data at an exchange, trading venue, market data provider, or trading technology vendor
- Practitioner-level knowledge of at least one asset class: commodities and environmental products; digital assets and event contracts; fixed income and structured products; equities and funds; or foreign exchange and money markets (including instruments, venues, trading conventions, and pricing)
- Understanding of front office workflows: execution, sales, research, and risk functions on a trading desk, including order handling, quoting, and hedging
- Knowledge of market abuse typologies: insider dealing, spoofing, layering, wash trading, front running, benchmark manipulation, and how they appear in trade, order, and market data
- Working knowledge of trading conduct rules: EU Market Abuse Regulation (MAR), Markets in Financial Instruments Directive (MiFID II), US CFTC and SEC rules
- Understanding of structured data modeling: trade, order, market, and reference data; quality issues; and modeling concepts such as entities, schemas, validation rules, and versioning
- Fluent English; other languages a strong plus
- Hands-on experience with agentic workflows is a plus
